Current manufacturing processes of solid active pharmaceutical ingredients (API) are inconsistent, inefficient, inflexible and are partially responsible for the high cost of manufacturing and, in turn, drug products incurred on patients. Existing API production technologies are based on batch configurations, not end-to-end, not integrated, have a large footprint, lack real-time process monitoring and feedback control, and are not capable of producing dose to dose drug concentration precision as necessitated by personalized health care models in a way that follows current Good Manufacturing Protocol (cGMP).
In addition, batch process dynamics that are not observable in lab or pilot-scale, such as high shear, imperfect mixing, and large temperature gradients, may unpredictably affect the performance of the scaled-up processes in detrimental ways. These lead to variable product quality, high labor costs and suboptimal use of raw materials and inventories. Furthermore, inconsistent batch-to-batch quality can lead to entire production batches being discarded (some estimate this cost to be 25% of Big and Generic Pharma's revenue stream).
Additionally, the pharmaceutical industry as a whole suffers from expensive and slow supply chains, in part due to labor-intensive and costly offline quality testing necessitated by a lack of rigorous process analytical tools (PAT) and automated quality control algorithm implementation in industrial batch operation units. These process limitations result in at least two serious public healthcare issues, including (1) worldwide drug shortages, and (2) under- and overdosing of drug prescriptions due to insufficient liquid or solid dosage variety.